Dawn of AI Marketing ?? #35 - Simulation Marketing

Nowadays, most AI systems are trained on 80% real-life data and 20% or less synthetic data, which is data generated in a computer simulation.

Gartner predicts that by 2030, our simulations of the real world will be so accurate that most AI will be trained on synthetic data, which is already today cheaper and better suited for machine learning.

How would simulation be effective in marketing?

• Picking the right copy and creative is currently an ongoing process in digital advertisement because customer behavior seems to change rapidly. Simulating the campaign's effectiveness regarding CPC, ROI, potential backlash, and ROAS would create more effective campaigns.
• Customer interviews are challenging to get, costly, and time-intensive; simulating them makes sense.
• Market strategy is complex because it is hard to predict black swans, adoption rates, and technology development speeds. Simulating multiple scenarios would give us a greater overview and potentially make us more antifragile.

In a nutshell ??

Digital Twins are detailed digital replicas of physical entities used to generate realistic synthetic data by simulating their behavior and conditions. This data is valuable for training AI models, testing systems, and preserving privacy without using sensitive real-world data.. Read More

Synthetic Organic Parity is a process for customer interviews involving organic and synthetic users. We recruit participants for organic interviews, identify common themes, and conduct qualitative and quantitative analyses. By summarizing insights from organic users and applying the same methodologies to synthetic users, we measure the overlap in themes, depth, comprehensiveness, and qualitative alignment. Our findings indicate that incorporating personal accounts and follow-up questions with synthetic users enhances their depth, making their responses more comparable to those from organic interviews Read More

World Models are neural networks that learn by observing and predicting, aiming to mimic human reasoning, planning, and action. Unlike LLMs, they focus on prediction rather than generation, deducing cause-and-effect and inferring scientific concepts like space and time. These models react reflexively, reason through problems, manage uncertainty, and calculate action costs using an energy score and intrinsic principles to guide behavior. Read More

I made this video using ChatGPT for the Lyrics, Suno AI for the soundtrack, and Pika AI for the footage.

Tips and Tricks ??

Synthetic Users -> Run user and market research with the most human-like AI participants.

AdCreative.ai -> Score your ad creatives before advertising, and let our AI predict which ones will perform better. Save on ad spend and increase ROI right from the start.

Native AI -> Create a digital twin of your customers to understand and predict consumer preferences & behaviors.

Content To Digest ??

Check out AI Marketing Lunch with David - AI and Growth Education #4, where David Arnoux talks about the process he automates as the CEO of Growth Tribe and how his fascination with using synthetic data, for example, customer interviews.

An employee of Open AI opened up about why he was fired.

If you are interested in the alignment problem, or Leopold vision on the development of AGI, check his website.

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